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OEM Experience
What do you like best about the product?
Version upgrade/update and up to date documentation
What do you dislike about the product?
Current cluster and fabric configuration can be tricky at times
What problems is the product solving and how is that benefiting you?
Neo4j provides the best and cleanest property graph implementations and pure graph theory feature/algorithms
Recommendations to others considering the product:
Changing to graph paradigm could be daunting, but neo4j is the right database for the journey
Very useful database that solves some complicated use cases for my enterprise
What do you like best about the product?
Neo4j focuses on the relationship aspect of data storage, which is convenient for the use case of my enterprise where we are trying to track the assets on our network and the relationships between those assets. Also, the suite of tools available speeds up development significantly. Spinning up a docker container and trying out data models and Cypher queries locally allows for quick developer growth for learning the Neo4j landscape.
What do you dislike about the product?
There is not much that I dislike about Neo4j other than having an open comparison between the benefits and downsides of using a graph database to solve certain problems vs others. Neo4j is great but it might not be ideal for every use case so transparency around when and where to use it would be great.
What problems is the product solving and how is that benefiting you?
In my enterprise we are trying to track all of the assets in our network and the relationships between those assets in near real-time with historical relationships.
Neo4Joe
What do you like best about the product?
Neo4j is a total solution space for me. Whereas some engineers use Excel to play with an idea, I feel Neo4j is superior tool for capturing reality and making modifications that ultimately result in a flexible working model. And then all operations can happen on the data in-place. So for a hackathon it`s a total cheat to start with Neo4j as a foundation. But equally, Neo4j has changed the way I think and has opened my mind to what is possible, and that`s because when you have the fundamental building blocks of nodes & edges, the sky is the limit. Oh, and cypher. It`s basically python in a database--really expressive, and powerful and fast.
What do you dislike about the product?
Okay, this isn`t really a dislike. It`s more a wish. I want it to be even easier for me to build simple web apps...just a javascript front end...no middle layer...but I would wish for a user authentication + authorization layer. So often I want to show something like an interactive chart, custom designed and publishable to the web.
What problems is the product solving and how is that benefiting you?
I am using Neo4j in a risk computation application. It helps to not have to ever send the data out of the database...but to just do the compute in-place. And it`s fast and easy to assess and explain how a partiular risk score is generated.
All connected
What do you like best about the product?
Easy and fast to deploy in productions. Many features to try and implement.
What do you dislike about the product?
Nothing in this moment. I only have used Db features
What problems is the product solving and how is that benefiting you?
Knowledge graph
Good and fun!
What do you like best about the product?
Connection, relationship discovery, apoc, data science applications.
Profiler is a life saver.
Profiler is a life saver.
What do you dislike about the product?
Bloom doesn't let me create new node types / relationships unless they exist currently in the graph.
The neo4j dekstop / web app performs quite terribly when loading data above a certain limit. Even if it's not in the node visualization tab. Not sure what the threshold is, but it's fairly frustrating (I assume it's due to unoptomized js).
Option to return only what I queried for in the graph at first load... For example, I might query (n:Person)--(m:Movie) and get back the relationships in the visualization by default, which is generally great, but sometimes I want to quickly see if I'm missing something in the return statement. Although I understand that adding that feature may cause more confusion than it's worth!
The neo4j dekstop / web app performs quite terribly when loading data above a certain limit. Even if it's not in the node visualization tab. Not sure what the threshold is, but it's fairly frustrating (I assume it's due to unoptomized js).
Option to return only what I queried for in the graph at first load... For example, I might query (n:Person)--(m:Movie) and get back the relationships in the visualization by default, which is generally great, but sometimes I want to quickly see if I'm missing something in the return statement. Although I understand that adding that feature may cause more confusion than it's worth!
What problems is the product solving and how is that benefiting you?
Modeling IoT device data and the device's relationship to actual entites along with the operational context. The performance has been good and, honestly, allows me to get away with more than I probably should. But I won't complain about that.
Thinking in graphs opens a whole new world
What do you like best about the product?
Coming from a traditionally RDBMS background, neo4j and graph databases have opened up new lines of thinking. The tools provided by neo4j make it very easy to get up and running quickly, and the free training programs they offer are second to none. They have well-documented drivers for a variety of popular languages.
What do you dislike about the product?
I'm not sure I can point to any particular things I dislike. It does require a shift in thinking from traditional RDBMS systems because you have to think more carefully about the problems you are trying to solve and the relationships between your data.
What problems is the product solving and how is that benefiting you?
neo4j is helping my team and me solve problems related to complex queries in a very large data set where how different data points are related to one another is key.
Native Graphdatabase, scalable, performant, professional service and support
What do you like best about the product?
Open-source community edition helps to start with Neo4j. Easy install, many tutorials and community blogs. Enterprise edition comes with additional features and professional support.
The native graph database is flexible, scalable and can easily transferred in a cloud instance, if necessary. Good documentation, as well as a big community.
ACID-compliant database.
In addition to the database, a native integration of GraphDataScience algorithms for machine learning, graph embeddings.
The database comes with a visualization, making it easy to start and to provide users with a user interface
Professional services, boot camps and other workshops can be booked.
There are cloud versions available for Google Cloud and AmazonWebServices.
The native graph database is flexible, scalable and can easily transferred in a cloud instance, if necessary. Good documentation, as well as a big community.
ACID-compliant database.
In addition to the database, a native integration of GraphDataScience algorithms for machine learning, graph embeddings.
The database comes with a visualization, making it easy to start and to provide users with a user interface
Professional services, boot camps and other workshops can be booked.
There are cloud versions available for Google Cloud and AmazonWebServices.
What do you dislike about the product?
Some of the features are only available for enterprise version including live-backup and role model.
While live-backup can be performed on a running database, for community edition the database has to be stopped. Which is ok for pilots and smaller systems. If you can not allow down time of the database you have to go for enterprise.
The role model can be handeled by an external or additional application layer.
While live-backup can be performed on a running database, for community edition the database has to be stopped. Which is ok for pilots and smaller systems. If you can not allow down time of the database you have to go for enterprise.
The role model can be handeled by an external or additional application layer.
What problems is the product solving and how is that benefiting you?
First of all the most important - connecting data (breaking data silos). Starting with meta data management which is obviously connected to raw data.
Connecting public data with in-house data we created a knowledge graph.
Connecting sensitive data from patients with public knowledge from literature.
Machine Learning on public and in-house data - including clustering, classification.
Connecting data from animal models, ontologies with patient data for translational research
Connecting public data with in-house data we created a knowledge graph.
Connecting sensitive data from patients with public knowledge from literature.
Machine Learning on public and in-house data - including clustering, classification.
Connecting data from animal models, ontologies with patient data for translational research
Recommendations to others considering the product:
Start with the community edition and built a quick pilot with your users. Involve them in data modeling - which is in most cases 99% of what they draw on white boards. Evolve from there.
Neo4j, The best Graph database out there
What do you like best about the product?
- Cypher Query
- Graph Visualisation
- The speed at which very large graphs are queried
- Python Connectivity
- The APPs available in Graph Apps Gallery
- Graph Visualisation
- The speed at which very large graphs are queried
- Python Connectivity
- The APPs available in Graph Apps Gallery
What do you dislike about the product?
- The Documentations could be improved with more practical examples
- The Setting is kinda complicated to understand
- Requires more RAM when processing huge datasets
- The Setting is kinda complicated to understand
- Requires more RAM when processing huge datasets
What problems is the product solving and how is that benefiting you?
I was building a recommendation system for my college project and processing data in conventional format was a bit difficult since the dataset was huge. Converting the dataset to graph database and connecting the dabase to python via Neo4j connector helped process the data much faster and come up with better results. I am looking forward to trying graph neural network programs by incorporating Neo4j with ML algorithms.
I worked on Neo4j for 8 years already, that is still be the best graph database in the world.
What do you like best about the product?
Cypher Query
Performance
Neo4j Web Console
Neo4j has been growing so fast, there are many great features produced by the team year by year.
Performance
Neo4j Web Console
Neo4j has been growing so fast, there are many great features produced by the team year by year.
What do you dislike about the product?
Documentation is worse now. We got some issues when upgrading to the newer version recently
What problems is the product solving and how is that benefiting you?
Contexting the data by Graph
Performance on our user function has been improved when moving from Postgres data to Neo4j
Performance on our user function has been improved when moving from Postgres data to Neo4j
I just loved it
What do you like best about the product?
When you are new to it, it is very easy to start with and get around. The community is growing, so if you are stuck, it is easy to overcome any challenge. The docs are awesome.
What do you dislike about the product?
Coming from relational to non-relational databases was weirder than this. Starting with Neo4j is completely different and way easier, but still can be simpler.
What problems is the product solving and how is that benefiting you?
We are moving our data around a lot, and Neo4j reduced our costs of development a lot. It is also very flexible
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